Výsledky vyhledávání - "GOMEZ, PABLO"

Report

Rapid Distributed Fine-tuning of a Segmentation Model Onboard Satellites

Autor: Plumridge, Meghan, Maråk, Rasmus, Ceccobello, Chiara, Gómez, Pablo, Meoni, Gabriele, Svoboda, Filip, Lane, Nicholas D.

Segmentation of Earth observation (EO) satellite data is critical for natural hazard analysis and disaster response. However, processing EO data at ground stations introduces delays due to data transmission bottlenecks and communication windows. Usin

Externí odkaz: http://arxiv.org/abs/2411.17831

Zobrazit plný text záznamu

Report

Machine learning-driven Anomaly Detection and Forecasting for Euclid Space Telescope Operations

Autor: Gómez, Pablo, Vavrek, Roland D., Buenadicha, Guillermo, Hoar, John, Kruk, Sandor, Reerink, Jan

State-of-the-art space science missions increasingly rely on automation due to spacecraft complexity and the costs of human oversight. The high volume of data, including scientific and telemetry data, makes manual inspection challenging. Machine lear

Externí odkaz: http://arxiv.org/abs/2411.05596

Zobrazit plný text záznamu

Report

Delving into the Utilisation of ChatGPT in Scientific Publications in Astronomy

Autor: Astarita, Simone, Kruk, Sandor, Reerink, Jan, Gómez, Pablo

Publikováno v: Proceedings of SPAICE2024 (2024) 241-246

Rapid progress in the capabilities of machine learning approaches in natural language processing has culminated in the rise of large language models over the last two years. Recent works have shown unprecedented adoption of these for academic writing

Externí odkaz: http://arxiv.org/abs/2406.17324

Zobrazit plný text záznamu

Report

XAMI -- A Benchmark Dataset for Artefact Detection in XMM-Newton Optical Images

Autor: Dima, Elisabeta-Iulia, Gómez, Pablo, Kruk, Sandor, Kretschmar, Peter, Rosen, Simon, Popa, Călin-Adrian

Reflected or scattered light produce artefacts in astronomical observations that can negatively impact the scientific study. Hence, automated detection of these artefacts is highly beneficial, especially with the increasing amounts of data gathered.

Externí odkaz: http://arxiv.org/abs/2406.17323

Zobrazit plný text záznamu

Report

Machine learning-based identification of Gaia astrometric exoplanet orbits

Autor: Sahlmann, Johannes, Gómez, Pablo

The third Gaia data release (DR3) contains $\sim$170 000 astrometric orbit solutions of two-body systems located within $\sim$500 pc of the Sun. Determining component masses in these systems, in particular of stars hosting exoplanets, usually hinges

Externí odkaz: http://arxiv.org/abs/2404.09350

Zobrazit plný text záznamu

Report

Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multicriteria Decision-Making Approach

Autor: Pérez-Pérez, Juan F., Gómez, Pablo Isaza, Bonet, Isis, Sánchez-Pinzón, María Solange, Caraffini, Fabio, Lochmuller, Christian

Climate risk assessment is becoming increasingly important. For organisations, identifying and assessing climate-related risks is challenging, as they can come from multiple sources. This study identifies and assesses the main climate transition risk

Externí odkaz: http://arxiv.org/abs/2404.16055

Zobrazit plný text záznamu